Random Forest Prediction Model

Open libraries.

library("mlbench")
library("dplyr")
library("caret")
library("randomForest")
library("lattice")
library("ggplot2")
library("rpart")
library("e1071")
library("caret", lib.loc="/Library/Frameworks/R.framework/Versions/3.4/Resources/library")
library("stats")
library(relaimpo)
library(party)

Get a list of Variable names.

Names <- names(dfNormDatAndFactor)
unlist(Names, recursive = TRUE, use.names = TRUE)
  [1] "Enrolling"                                                                       
  [2] "Sex.F"                                                                           
  [3] "Sex.M"                                                                           
  [4] "Expel.N"                                                                         
  [5] "Expel.Y"                                                                         
  [6] "First.Gen.N"                                                                     
  [7] "First.Gen.Y"                                                                     
  [8] "Challenge.Tag.N"                                                                 
  [9] "Challenge.Tag.Y"                                                                 
 [10] "Boettcher.Semi.N"                                                                
 [11] "Boettcher.Semi.Y"                                                                
 [12] "Boettcher.Final.N"                                                               
 [13] "Boettcher.Final.Y"                                                               
 [14] "Daniels.Semi.N"                                                                  
 [15] "Daniels.Semi.Y"                                                                  
 [16] "Daniels.Final.N"                                                                 
 [17] "Daniels.Final.Y"                                                                 
 [18] "Harvey.App.N"                                                                    
 [19] "Harvey.App.Y"                                                                    
 [20] "Harvey.Final.N"                                                                  
 [21] "Harvey.Final.Y"                                                                  
 [22] "FC.App.N"                                                                        
 [23] "FC.App.Y"                                                                        
 [24] "Thorson.App.N"                                                                   
 [25] "Thorson.App.Y"                                                                   
 [26] "Thorson.Admit.N"                                                                 
 [27] "Thorson.Admit.Y"                                                                 
 [28] "Summet.Participant.N"                                                            
 [29] "Summet.Participant.Y"                                                            
 [30] "Mines.Medal.N"                                                                   
 [31] "Mines.Medal.Y"                                                                   
 [32] "SPS.N"                                                                           
 [33] "SPS.Y"                                                                           
 [34] "Veteran.N"                                                                       
 [35] "Veteran.Y"                                                                       
 [36] "Legacy.N"                                                                        
 [37] "Legacy.Y"                                                                        
 [38] "Athlete.N"                                                                       
 [39] "Athlete.Y"                                                                       
 [40] "State.CO"                                                                        
 [41] "State.Other"                                                                     
 [42] "Citizenship.Foreign.National.International"                                      
 [43] "Citizenship.International"                                                       
 [44] "Citizenship.Missing"                                                             
 [45] "Citizenship.U.S..Citizen"                                                        
 [46] "Citizenship.U.S..Permanent.Resident.Green.Card.Holder"                           
 [47] "Citizenship.Undocumented.DACA"                                                   
 [48] "Ethnicity.American.Indian.or.Alaska.Native"                                      
 [49] "Ethnicity.Asian"                                                                 
 [50] "Ethnicity.Black.or.African.American"                                             
 [51] "Ethnicity.Hispanic.or.Latino"                                                    
 [52] "Ethnicity.Missing"                                                               
 [53] "Ethnicity.Multiracial"                                                           
 [54] "Ethnicity.Native.Hawaiian.or.Other.Pacific.Islander"                             
 [55] "Ethnicity.NotDeclared"                                                           
 [56] "Ethnicity.Unknown"                                                               
 [57] "Ethnicity.White"                                                                 
 [58] "Major.App.Applied.Mathematics...Statistics...Computational...Applied.Mathematics"
 [59] "Major.App.Applied.Mathematics...Statistics...Statistics"                         
 [60] "Major.App.Chemical.Engineering"                                                  
 [61] "Major.App.Chemical.Engineering...Biological.Engineering.Specialty"               
 [62] "Major.App.Chemistry"                                                             
 [63] "Major.App.Chemistry...Biochemistry.Specialty"                                    
 [64] "Major.App.Chemistry...Environmental.Chemistry.Specialty"                         
 [65] "Major.App.Civil.Engineering"                                                     
 [66] "Major.App.Computer.Science"                                                      
 [67] "Major.App.Economics"                                                             
 [68] "Major.App.Electrical.Engineering"                                                
 [69] "Major.App.Engineering.Physics"                                                   
 [70] "Major.App.Environmental.Engineering"                                             
 [71] "Major.App.Geological.Engineering"                                                
 [72] "Major.App.Geophysical.Engineering"                                               
 [73] "Major.App.Mechanical.Engineering"                                                
 [74] "Major.App.Metallurgical...Materials.Engineering"                                 
 [75] "Major.App.Mining.Engineering"                                                    
 [76] "Major.App.Missing"                                                               
 [77] "Major.App.Petroleum.Engineering"                                                 
 [78] "Major.App.Undecided"                                                             
 [79] "First.Contact.ACT"                                                               
 [80] "First.Contact.Application"                                                       
 [81] "First.Contact.Athlete.Form"                                                      
 [82] "First.Contact.Campus.Visit"                                                      
 [83] "First.Contact.College.Fair"                                                      
 [84] "First.Contact.FUF"                                                               
 [85] "First.Contact.Girls.Lead.the.Way"                                                
 [86] "First.Contact.GPA.Form"                                                          
 [87] "First.Contact.Inquiry.Form"                                                      
 [88] "First.Contact.Mailing"                                                           
 [89] "First.Contact.Materials"                                                         
 [90] "First.Contact.MEP"                                                               
 [91] "First.Contact.Phone"                                                             
 [92] "First.Contact.Preview.Mines"                                                     
 [93] "First.Contact.Royall.Search"                                                     
 [94] "First.Contact.SAT"                                                               
 [95] "First.Contact.TOEFL"                                                             
 [96] "First.Visit.Campus.Tour"                                                         
 [97] "First.Visit.Campus.Visit"                                                        
 [98] "First.Visit.Class.Shadow"                                                        
 [99] "First.Visit.Discover.Mines"                                                      
[100] "First.Visit.Discovery.Mines.in.Your.City"                                        
[101] "First.Visit.Girls.Lead.the.Way"                                                  
[102] "First.Visit.Launch"                                                              
[103] "First.Visit.Making.The.Connection"                                               
[104] "First.Visit.Meet.Me.at.Mines"                                                    
[105] "First.Visit.None"                                                                
[106] "First.Visit.Preview.Mines"                                                       
[107] "First.Visit.Preview.Mines.In.Your.City"                                          
[108] "Sport.Men.s.Varsity.Baseball"                                                    
[109] "Sport.Men.s.Varsity.Basketball"                                                  
[110] "Sport.Men.s.Varsity.Football"                                                    
[111] "Sport.Men.s.Varsity.Golf"                                                        
[112] "Sport.Men.s.Varsity.Soccer"                                                      
[113] "Sport.Men.s.Varsity.Wrestling"                                                   
[114] "Sport.None"                                                                      
[115] "Sport.Varsity.Swimming.Diving"                                                   
[116] "Sport.Varsity.Track.Field"                                                       
[117] "Sport.Varsity.XCountry"                                                          
[118] "Sport.Women.s.Varsity.Basketball"                                                
[119] "Sport.Women.s.Varsity.Soccer"                                                    
[120] "Sport.Women.s.Varsity.Softball"                                                  
[121] "Sport.Women.s.Varsity.Volleyball"                                                
[122] "App.Created.Days"                                                                
[123] "Age"                                                                             
[124] "HS.GPA"                                                                          
[125] "SATR.Converted"                                                                  
[126] "Review.OutsideActivity"                                                          
[127] "Review.Leadership"                                                               
[128] "Review.WorkExp"                                                                  
[129] "Review.WorkEthic"                                                                
[130] "Review.ExpDiversity"                                                             
[131] "Review.DesireAttend"                                                             
[132] "Review.Affinity"                                                                 
[133] "Review.InnovEntrep"                                                              
[134] "Review.Teamwork"                                                                 
[135] "Review.OverallFit"                                                               
[136] "Logins.60Days"                                                                   
[137] "EventCount.All"                                                                  
[138] "EventCount.Admitted"                                                             
[139] "EventCount.Campus"                                                               

Parrtitions created with 75% of data for training and 25% of data for testing.

inTraining <- createDataPartition(dfNormDatAndFactor$Enrolling, p = 0.75, list = FALSE)
training <- dfNormDatAndFactor[inTraining, ]
testing <- dfNormDatAndFactor[-inTraining, ]
training
testing

Run Random Forest Model with all variables.

rfModel <- randomForest(Enrolling ~ Sex.F + Sex.M +Expel.N + Expel.Y+ First.Gen.N+ First.Gen.Y+Challenge.Tag.N + Challenge.Tag.Y+ Boettcher.Semi.N+ Boettcher.Semi.Y+ Boettcher.Final.N+Boettcher.Final.Y + Daniels.Semi.N+Daniels.Semi.Y+ Daniels.Final.N+ Daniels.Final.Y+ Harvey.App.N+ Harvey.App.Y + Harvey.Final.N+ Harvey.Final.Y+ FC.App.N+ FC.App.Y+  Thorson.App.N+ Thorson.App.Y+ Thorson.Admit.N +Thorson.Admit.Y+Summet.Participant.N+ Summet.Participant.Y + Mines.Medal.N+ Mines.Medal.Y+ SPS.N+ SPS.Y+ Veteran.N+ Veteran.Y+ Legacy.N +  Legacy.Y+ Athlete.N +  Athlete.N + Athlete.Y + State.CO +  State.Other  +  Citizenship.Foreign.National.International +Citizenship.International +  Citizenship.Missing+ Citizenship.U.S..Citizen+ Citizenship.U.S..Permanent.Resident.Green.Card.Holder+ Citizenship.Undocumented.DACA+ Ethnicity.American.Indian.or.Alaska.Native+  Ethnicity.Asian+ Ethnicity.Black.or.African.American+ Ethnicity.Hispanic.or.Latino + Ethnicity.Missing + Ethnicity.Multiracial +Ethnicity.Native.Hawaiian.or.Other.Pacific.Islander + Ethnicity.NotDeclared + Ethnicity.Unknown +Ethnicity.White+ Major.App.Applied.Mathematics...Statistics...Computational...Applied.Mathematics+ Major.App.Applied.Mathematics...Statistics...Statistics+ Major.App.Chemical.Engineering+ Major.App.Chemical.Engineering...Biological.Engineering.Specialty+ Major.App.Chemistry+  Major.App.Chemistry...Biochemistry.Specialty + Major.App.Chemistry...Environmental.Chemistry.Specialty + Major.App.Civil.Engineering + Major.App.Computer.Science + Major.App.Economics+ Major.App.Electrical.Engineering+ Major.App.Engineering.Physics+  Major.App.Environmental.Engineering+ Major.App.Geological.Engineering +  Major.App.Geophysical.Engineering +Major.App.Mechanical.Engineering +  Major.App.Metallurgical...Materials.Engineering + Major.App.Mining.Engineering +  Major.App.Missing + Major.App.Petroleum.Engineering+   Major.App.Undecided+ First.Contact.ACT +  First.Contact.Application + First.Contact.Athlete.Form + First.Contact.Campus.Visit + First.Contact.College.Fair + First.Contact.FUF+First.Contact.Girls.Lead.the.Way+First.Contact.GPA.Form + First.Contact.Inquiry.Form+First.Contact.Mailing+ First.Contact.Materials +  First.Contact.MEP+ First.Contact.Phone+ First.Contact.Preview.Mines+ First.Contact.Royall.Search+First.Contact.TOEFL+ First.Contact.SAT+ First.Visit.Campus.Tour+ First.Visit.Campus.Visit+ First.Visit.Class.Shadow +  First.Visit.Discover.Mines+ First.Visit.Discovery.Mines.in.Your.City+ First.Visit.Girls.Lead.the.Way+  First.Visit.Launch + First.Visit.Making.The.Connection + First.Visit.Meet.Me.at.Mines+ First.Visit.None+  First.Visit.Preview.Mines + First.Visit.Preview.Mines.In.Your.City + Sport.Men.s.Varsity.Baseball+  Sport.Men.s.Varsity.Basketball+  Sport.Men.s.Varsity.Football + Sport.Men.s.Varsity.Golf +Sport.Men.s.Varsity.Soccer+  Sport.Men.s.Varsity.Wrestling+  Sport.None+  Sport.Varsity.Swimming.Diving+ Sport.Varsity.Track.Field+Sport.Varsity.XCountry+  Sport.Women.s.Varsity.Basketball +  Sport.Women.s.Varsity.Soccer+  Sport.Women.s.Varsity.Softball + Sport.Women.s.Varsity.Volleyball+ App.Created.Days +  Age  + HS.GPA+ SATR.Converted +Review.OutsideActivity +Review.Leadership+Review.WorkExp+ Review.WorkEthic +Review.ExpDiversity +Review.DesireAttend +Review.Affinity+ Review.InnovEntrep+Review.Teamwork +Review.OverallFit + Logins.60Days+EventCount.All+EventCount.Admitted+EventCount.Campus, data =  training)
rfModel

Call:
 randomForest(formula = Enrolling ~ Sex.F + Sex.M + Expel.N +      Expel.Y + First.Gen.N + First.Gen.Y + Challenge.Tag.N + Challenge.Tag.Y +      Boettcher.Semi.N + Boettcher.Semi.Y + Boettcher.Final.N +      Boettcher.Final.Y + Daniels.Semi.N + Daniels.Semi.Y + Daniels.Final.N +      Daniels.Final.Y + Harvey.App.N + Harvey.App.Y + Harvey.Final.N +      Harvey.Final.Y + FC.App.N + FC.App.Y + Thorson.App.N + Thorson.App.Y +      Thorson.Admit.N + Thorson.Admit.Y + Summet.Participant.N +      Summet.Participant.Y + Mines.Medal.N + Mines.Medal.Y + SPS.N +      SPS.Y + Veteran.N + Veteran.Y + Legacy.N + Legacy.Y + Athlete.N +      Athlete.N + Athlete.Y + State.CO + State.Other + Citizenship.Foreign.National.International +      Citizenship.International + Citizenship.Missing + Citizenship.U.S..Citizen +      Citizenship.U.S..Permanent.Resident.Green.Card.Holder + Citizenship.Undocumented.DACA +      Ethnicity.American.Indian.or.Alaska.Native + Ethnicity.Asian +      Ethnicity.Black.or.African.American + Ethnicity.Hispanic.or.Latino +      Ethnicity.Missing + Ethnicity.Multiracial + Ethnicity.Native.Hawaiian.or.Other.Pacific.Islander +      Ethnicity.NotDeclared + Ethnicity.Unknown + Ethnicity.White +      Major.App.Applied.Mathematics...Statistics...Computational...Applied.Mathematics +      Major.App.Applied.Mathematics...Statistics...Statistics +      Major.App.Chemical.Engineering + Major.App.Chemical.Engineering...Biological.Engineering.Specialty +      Major.App.Chemistry + Major.App.Chemistry...Biochemistry.Specialty +      Major.App.Chemistry...Environmental.Chemistry.Specialty +      Major.App.Civil.Engineering + Major.App.Computer.Science +      Major.App.Economics + Major.App.Electrical.Engineering +      Major.App.Engineering.Physics + Major.App.Environmental.Engineering +      Major.App.Geological.Engineering + Major.App.Geophysical.Engineering +      Major.App.Mechanical.Engineering + Major.App.Metallurgical...Materials.Engineering +      Major.App.Mining.Engineering + Major.App.Missing + Major.App.Petroleum.Engineering +      Major.App.Undecided + First.Contact.ACT + First.Contact.Application +      First.Contact.Athlete.Form + First.Contact.Campus.Visit +      First.Contact.College.Fair + First.Contact.FUF + First.Contact.Girls.Lead.the.Way +      First.Contact.GPA.Form + First.Contact.Inquiry.Form + First.Contact.Mailing +      First.Contact.Materials + First.Contact.MEP + First.Contact.Phone +      First.Contact.Preview.Mines + First.Contact.Royall.Search +      First.Contact.TOEFL + First.Contact.SAT + First.Visit.Campus.Tour +      First.Visit.Campus.Visit + First.Visit.Class.Shadow + First.Visit.Discover.Mines +      First.Visit.Discovery.Mines.in.Your.City + First.Visit.Girls.Lead.the.Way +      First.Visit.Launch + First.Visit.Making.The.Connection +      First.Visit.Meet.Me.at.Mines + First.Visit.None + First.Visit.Preview.Mines +      First.Visit.Preview.Mines.In.Your.City + Sport.Men.s.Varsity.Baseball +      Sport.Men.s.Varsity.Basketball + Sport.Men.s.Varsity.Football +      Sport.Men.s.Varsity.Golf + Sport.Men.s.Varsity.Soccer + Sport.Men.s.Varsity.Wrestling +      Sport.None + Sport.Varsity.Swimming.Diving + Sport.Varsity.Track.Field +      Sport.Varsity.XCountry + Sport.Women.s.Varsity.Basketball +      Sport.Women.s.Varsity.Soccer + Sport.Women.s.Varsity.Softball +      Sport.Women.s.Varsity.Volleyball + App.Created.Days + Age +      HS.GPA + SATR.Converted + Review.OutsideActivity + Review.Leadership +      Review.WorkExp + Review.WorkEthic + Review.ExpDiversity +      Review.DesireAttend + Review.Affinity + Review.InnovEntrep +      Review.Teamwork + Review.OverallFit + Logins.60Days + EventCount.All +      EventCount.Admitted + EventCount.Campus, data = training) 
               Type of random forest: classification
                     Number of trees: 500
No. of variables tried at each split: 11

        OOB estimate of  error rate: 8.62%
Confusion matrix:
     N   Y class.error
N 3563 127  0.03441734
Y  276 711  0.27963526
rfModel.prediction <- predict(rfModel, testing)
table(rfModel.prediction, testing$Enrolling)
                  
rfModel.prediction    N    Y
                 N 1181   96
                 Y   48  233

To determine variable importance.

imprfModel <-   importance(rfModel)
imprfModel
                                                                                 MeanDecreaseGini
Sex.F                                                                                7.437706e+00
Sex.M                                                                                7.970186e+00
Expel.N                                                                              8.659331e-01
Expel.Y                                                                              9.745556e-01
First.Gen.N                                                                          5.083216e+00
First.Gen.Y                                                                          5.162621e+00
Challenge.Tag.N                                                                      2.142498e+00
Challenge.Tag.Y                                                                      2.090986e+00
Boettcher.Semi.N                                                                     1.268805e+00
Boettcher.Semi.Y                                                                     1.088516e+00
Boettcher.Final.N                                                                    4.735714e-01
Boettcher.Final.Y                                                                    4.705432e-01
Daniels.Semi.N                                                                       1.967173e+00
Daniels.Semi.Y                                                                       1.647909e+00
Daniels.Final.N                                                                      4.607632e-01
Daniels.Final.Y                                                                      3.839780e-01
Harvey.App.N                                                                         4.454943e+00
Harvey.App.Y                                                                         4.307206e+00
Harvey.Final.N                                                                       1.489947e+00
Harvey.Final.Y                                                                       1.734864e+00
FC.App.N                                                                             2.932341e+00
FC.App.Y                                                                             3.056475e+00
Thorson.App.N                                                                        6.108025e+00
Thorson.App.Y                                                                        5.748607e+00
Thorson.Admit.N                                                                      5.450054e+00
Thorson.Admit.Y                                                                      5.647499e+00
Summet.Participant.N                                                                 8.726508e-01
Summet.Participant.Y                                                                 8.859990e-01
Mines.Medal.N                                                                        9.469697e-05
Mines.Medal.Y                                                                        3.118012e-04
SPS.N                                                                                1.104065e+00
SPS.Y                                                                                1.168917e+00
Veteran.N                                                                            3.948454e+00
Veteran.Y                                                                            3.933734e+00
Legacy.N                                                                             6.212300e+00
Legacy.Y                                                                             6.580279e+00
Athlete.N                                                                            6.485726e+00
Athlete.Y                                                                            6.714595e+00
State.CO                                                                             3.247304e+01
State.Other                                                                          2.920199e+01
Citizenship.Foreign.National.International                                           3.876040e+00
Citizenship.International                                                            3.288128e-01
Citizenship.Missing                                                                  2.853720e+00
Citizenship.U.S..Citizen                                                             5.462649e+00
Citizenship.U.S..Permanent.Resident.Green.Card.Holder                                1.888712e+00
Citizenship.Undocumented.DACA                                                        1.307468e-01
Ethnicity.American.Indian.or.Alaska.Native                                           1.831798e+00
Ethnicity.Asian                                                                      4.660927e+00
Ethnicity.Black.or.African.American                                                  1.244916e+00
Ethnicity.Hispanic.or.Latino                                                         3.141938e+00
Ethnicity.Missing                                                                    4.584504e-01
Ethnicity.Multiracial                                                                0.000000e+00
Ethnicity.Native.Hawaiian.or.Other.Pacific.Islander                                  1.931345e-01
Ethnicity.NotDeclared                                                                3.649621e+00
Ethnicity.Unknown                                                                    0.000000e+00
Ethnicity.White                                                                      7.932935e+00
Major.App.Applied.Mathematics...Statistics...Computational...Applied.Mathematics     1.583910e+00
Major.App.Applied.Mathematics...Statistics...Statistics                              8.705972e-01
Major.App.Chemical.Engineering                                                       7.347701e+00
Major.App.Chemical.Engineering...Biological.Engineering.Specialty                    5.192139e+00
Major.App.Chemistry                                                                  1.054614e+00
Major.App.Chemistry...Biochemistry.Specialty                                         1.475858e+00
Major.App.Chemistry...Environmental.Chemistry.Specialty                              2.618606e-01
Major.App.Civil.Engineering                                                          4.720395e+00
Major.App.Computer.Science                                                           4.695704e+00
Major.App.Economics                                                                  1.010823e+00
Major.App.Electrical.Engineering                                                     3.748680e+00
Major.App.Engineering.Physics                                                        5.395229e+00
Major.App.Environmental.Engineering                                                  3.140402e+00
Major.App.Geological.Engineering                                                     2.851079e+00
Major.App.Geophysical.Engineering                                                    7.893425e-01
Major.App.Mechanical.Engineering                                                     8.485352e+00
Major.App.Metallurgical...Materials.Engineering                                      2.134452e+00
Major.App.Mining.Engineering                                                         2.443291e+00
Major.App.Missing                                                                    2.788781e+00
Major.App.Petroleum.Engineering                                                      4.397457e+00
Major.App.Undecided                                                                  5.302115e+00
First.Contact.ACT                                                                    6.692925e+00
First.Contact.Application                                                            8.421762e+00
First.Contact.Athlete.Form                                                           1.114967e+00
First.Contact.Campus.Visit                                                           1.347537e+01
First.Contact.College.Fair                                                           2.625882e-01
First.Contact.FUF                                                                    7.978287e+00
First.Contact.Girls.Lead.the.Way                                                     5.371549e-01
First.Contact.GPA.Form                                                               8.735425e-01
First.Contact.Inquiry.Form                                                           2.369550e+00
First.Contact.Mailing                                                                5.415302e-01
First.Contact.Materials                                                              3.451884e-01
First.Contact.MEP                                                                    8.260278e-01
First.Contact.Phone                                                                  2.024735e-02
First.Contact.Preview.Mines                                                          1.464733e+00
First.Contact.Royall.Search                                                          1.072953e+01
First.Contact.TOEFL                                                                  7.034645e-01
First.Contact.SAT                                                                    1.420114e+00
First.Visit.Campus.Tour                                                              1.370637e+01
First.Visit.Campus.Visit                                                             1.480266e+01
First.Visit.Class.Shadow                                                             2.329774e+00
First.Visit.Discover.Mines                                                           7.929069e+00
First.Visit.Discovery.Mines.in.Your.City                                             1.363295e+00
First.Visit.Girls.Lead.the.Way                                                       5.880593e-01
First.Visit.Launch                                                                   4.658352e+01
First.Visit.Making.The.Connection                                                    4.584449e+00
First.Visit.Meet.Me.at.Mines                                                         1.263360e+00
First.Visit.None                                                                     6.927932e+01
First.Visit.Preview.Mines                                                            6.506139e+00
First.Visit.Preview.Mines.In.Your.City                                               1.782319e+01
Sport.Men.s.Varsity.Baseball                                                         1.934009e-01
Sport.Men.s.Varsity.Basketball                                                       4.905744e-01
Sport.Men.s.Varsity.Football                                                         2.877780e+00
Sport.Men.s.Varsity.Golf                                                             2.163090e-01
Sport.Men.s.Varsity.Soccer                                                           4.367005e-01
Sport.Men.s.Varsity.Wrestling                                                        6.442545e-01
Sport.None                                                                           6.618847e+00
Sport.Varsity.Swimming.Diving                                                        1.314591e-02
Sport.Varsity.Track.Field                                                            2.996113e-01
Sport.Varsity.XCountry                                                               9.709506e-02
Sport.Women.s.Varsity.Basketball                                                     4.858711e-01
Sport.Women.s.Varsity.Soccer                                                         3.653904e-01
Sport.Women.s.Varsity.Softball                                                       1.199113e-02
Sport.Women.s.Varsity.Volleyball                                                     5.702375e-01
App.Created.Days                                                                     5.761980e+01
Age                                                                                  4.282867e+01
HS.GPA                                                                               6.344325e+01
SATR.Converted                                                                       4.569617e+01
Review.OutsideActivity                                                               1.585565e+01
Review.Leadership                                                                    1.912368e+01
Review.WorkExp                                                                       1.929378e+01
Review.WorkEthic                                                                     1.537185e+01
Review.ExpDiversity                                                                  1.606620e+01
Review.DesireAttend                                                                  2.316809e+01
Review.Affinity                                                                      1.992175e+01
Review.InnovEntrep                                                                   1.495064e+01
Review.Teamwork                                                                      1.910074e+01
Review.OverallFit                                                                    2.497267e+01
Logins.60Days                                                                        1.379456e+00
EventCount.All                                                                       1.642425e+02
EventCount.Admitted                                                                  2.249928e+02
EventCount.Campus                                                                    1.435702e+02
#format((sort(imprfModel, decreasing=TRUE)), scientific=F)
#sort(imprfModel, decreasing=TRUE)  # relative importance
dfimprfModel <-as.data.frame(imprfModel)
dfimprfModel
confusionMatrix(table(rfModel.prediction, testing$Enrolling))
Confusion Matrix and Statistics

                  
rfModel.prediction    N    Y
                 N 1181   96
                 Y   48  233
                                          
               Accuracy : 0.9076          
                 95% CI : (0.8921, 0.9215)
    No Information Rate : 0.7888          
    P-Value [Acc > NIR] : < 2.2e-16       
                                          
                  Kappa : 0.7069          
 Mcnemar's Test P-Value : 8.978e-05       
                                          
            Sensitivity : 0.9609          
            Specificity : 0.7082          
         Pos Pred Value : 0.9248          
         Neg Pred Value : 0.8292          
             Prevalence : 0.7888          
         Detection Rate : 0.7580          
   Detection Prevalence : 0.8196          
      Balanced Accuracy : 0.8346          
                                          
       'Positive' Class : N               
                                          

Plot of importance of Variabels.

varImpPlot(rfModel,cex = .6, pt.cex = .7, color = "navy blue", gcolor = par("fg"), lcolor = "gray", main = "Variable Importance for Random Forest Model")

Model with less variables

rfModelLess <- randomForest(Enrolling ~ State.CO +  State.Other  +  Major.App.Mechanical.Engineering +  First.Contact.Application + First.Contact.Campus.Visit + First.Contact.FUF + First.Contact.Royall.Search+ First.Visit.Campus.Tour+ First.Visit.Campus.Visit+ First.Visit.Discover.Mines+ First.Visit.Launch + First.Visit.None+  First.Visit.Preview.Mines.In.Your.City + App.Created.Days +  Age  + HS.GPA+ SATR.Converted +Review.OutsideActivity +Review.Leadership+Review.WorkExp+ Review.WorkEthic +Review.ExpDiversity +Review.DesireAttend +Review.Affinity+ Review.InnovEntrep+Review.Teamwork +Review.OverallFit +Ethnicity.White +EventCount.All+EventCount.Admitted+EventCount.Campus, data =  training)
rfModelLess

Call:
 randomForest(formula = Enrolling ~ State.CO + State.Other + Major.App.Mechanical.Engineering +      First.Contact.Application + First.Contact.Campus.Visit +      First.Contact.FUF + First.Contact.Royall.Search + First.Visit.Campus.Tour +      First.Visit.Campus.Visit + First.Visit.Discover.Mines + First.Visit.Launch +      First.Visit.None + First.Visit.Preview.Mines.In.Your.City +      App.Created.Days + Age + HS.GPA + SATR.Converted + Review.OutsideActivity +      Review.Leadership + Review.WorkExp + Review.WorkEthic + Review.ExpDiversity +      Review.DesireAttend + Review.Affinity + Review.InnovEntrep +      Review.Teamwork + Review.OverallFit + Ethnicity.White + EventCount.All +      EventCount.Admitted + EventCount.Campus, data = training) 
               Type of random forest: classification
                     Number of trees: 500
No. of variables tried at each split: 5

        OOB estimate of  error rate: 8.51%
Confusion matrix:
     N   Y class.error
N 3563 127  0.03441734
Y  271 716  0.27456940
rfModelLess.prediction <- predict(rfModelLess, testing)
table(rfModelLess.prediction, testing$Enrolling)
                      
rfModelLess.prediction    N    Y
                     N 1183   98
                     Y   46  231

To determine variable imortance.

imprfModelLess <-   importance(rfModelLess)
#format(imprfModelLess, scientific=F)
imprfModelLess
                                       MeanDecreaseGini
State.CO                                      30.878949
State.Other                                   29.257083
Major.App.Mechanical.Engineering              12.579230
First.Contact.Application                     11.785755
First.Contact.Campus.Visit                    15.618481
First.Contact.FUF                              9.576268
First.Contact.Royall.Search                   15.563429
First.Visit.Campus.Tour                       15.820761
First.Visit.Campus.Visit                      19.779964
First.Visit.Discover.Mines                     9.325906
First.Visit.Launch                            55.597020
First.Visit.None                              82.567953
First.Visit.Preview.Mines.In.Your.City        16.833940
App.Created.Days                              85.972986
Age                                           65.084346
HS.GPA                                        98.868442
SATR.Converted                                72.984411
Review.OutsideActivity                        21.638767
Review.Leadership                             29.026726
Review.WorkExp                                28.769419
Review.WorkEthic                              22.232976
Review.ExpDiversity                           22.870812
Review.DesireAttend                           32.226286
Review.Affinity                               29.324082
Review.InnovEntrep                            23.136576
Review.Teamwork                               28.812416
Review.OverallFit                             37.286821
Ethnicity.White                               14.279990
EventCount.All                               193.936731
EventCount.Admitted                          238.199556
EventCount.Campus                            157.806502
confusionMatrix(table(rfModelLess.prediction, testing$Enrolling))
Confusion Matrix and Statistics

                      
rfModelLess.prediction    N    Y
                     N 1183   98
                     Y   46  231
                                          
               Accuracy : 0.9076          
                 95% CI : (0.8921, 0.9215)
    No Information Rate : 0.7888          
    P-Value [Acc > NIR] : < 2.2e-16       
                                          
                  Kappa : 0.7055          
 Mcnemar's Test P-Value : 2.138e-05       
                                          
            Sensitivity : 0.9626          
            Specificity : 0.7021          
         Pos Pred Value : 0.9235          
         Neg Pred Value : 0.8339          
             Prevalence : 0.7888          
         Detection Rate : 0.7593          
   Detection Prevalence : 0.8222          
      Balanced Accuracy : 0.8323          
                                          
       'Positive' Class : N               
                                          

Model with top 25 variables

rfModelTop25 <- randomForest(Enrolling ~ State.CO +  State.Other  +  First.Contact.Campus.Visit + First.Visit.Campus.Tour+ First.Visit.Campus.Visit+ First.Visit.Discover.Mines+ First.Visit.Launch + First.Visit.None+  First.Visit.Preview.Mines.In.Your.City + App.Created.Days +  Age  + HS.GPA+ SATR.Converted +Review.OutsideActivity +Review.Leadership+Review.WorkExp+ Review.WorkEthic +Review.ExpDiversity +Review.DesireAttend +Review.Affinity+ Review.InnovEntrep+Review.Teamwork +Review.OverallFit +EventCount.All+EventCount.Admitted+EventCount.Campus, data =  training)
rfModelTop25

Call:
 randomForest(formula = Enrolling ~ State.CO + State.Other + First.Contact.Campus.Visit +      First.Visit.Campus.Tour + First.Visit.Campus.Visit + First.Visit.Discover.Mines +      First.Visit.Launch + First.Visit.None + First.Visit.Preview.Mines.In.Your.City +      App.Created.Days + Age + HS.GPA + SATR.Converted + Review.OutsideActivity +      Review.Leadership + Review.WorkExp + Review.WorkEthic + Review.ExpDiversity +      Review.DesireAttend + Review.Affinity + Review.InnovEntrep +      Review.Teamwork + Review.OverallFit + EventCount.All + EventCount.Admitted +      EventCount.Campus, data = training) 
               Type of random forest: classification
                     Number of trees: 500
No. of variables tried at each split: 5

        OOB estimate of  error rate: 8.66%
Confusion matrix:
     N   Y class.error
N 3565 125  0.03387534
Y  280 707  0.28368794
rfModelTop25.prediction <- predict(rfModelTop25, testing)
table(rfModelTop25.prediction, testing$Enrolling)
                       
rfModelTop25.prediction    N    Y
                      N 1182   98
                      Y   47  231

To determine variable imortance.

imprfModelTop25 <-   importance(rfModelTop25)
#format(imprfModelLess, scientific=F)
imprfModelTop25
                                       MeanDecreaseGini
State.CO                                       32.81859
State.Other                                    29.26938
First.Contact.Campus.Visit                     16.71002
First.Visit.Campus.Tour                        16.26760
First.Visit.Campus.Visit                       21.30551
First.Visit.Discover.Mines                     10.33880
First.Visit.Launch                             53.72968
First.Visit.None                               76.59342
First.Visit.Preview.Mines.In.Your.City         17.63941
App.Created.Days                               97.41080
Age                                            70.79303
HS.GPA                                        108.79595
SATR.Converted                                 79.43763
Review.OutsideActivity                         22.15891
Review.Leadership                              30.39901
Review.WorkExp                                 31.24720
Review.WorkEthic                               23.82738
Review.ExpDiversity                            23.54627
Review.DesireAttend                            32.95253
Review.Affinity                                30.80140
Review.InnovEntrep                             24.81996
Review.Teamwork                                30.19490
Review.OverallFit                              39.41873
EventCount.All                                198.86630
EventCount.Admitted                           252.81695
EventCount.Campus                             157.31704
confusionMatrix(table(rfModelTop25.prediction, testing$Enrolling))
Confusion Matrix and Statistics

                       
rfModelTop25.prediction    N    Y
                      N 1182   98
                      Y   47  231
                                          
               Accuracy : 0.9069          
                 95% CI : (0.8914, 0.9209)
    No Information Rate : 0.7888          
    P-Value [Acc > NIR] : < 2.2e-16       
                                          
                  Kappa : 0.7038          
 Mcnemar's Test P-Value : 3.292e-05       
                                          
            Sensitivity : 0.9618          
            Specificity : 0.7021          
         Pos Pred Value : 0.9234          
         Neg Pred Value : 0.8309          
             Prevalence : 0.7888          
         Detection Rate : 0.7587          
   Detection Prevalence : 0.8216          
      Balanced Accuracy : 0.8319          
                                          
       'Positive' Class : N               
                                          
PredictionTop25 <- cbind(rfModelTop25.prediction,testing)
PredictionTop25
---
title: "Random Forest"
output: html_notebook
---
##Random Forest Prediction Model

Open libraries.

```{r}
library("mlbench")
library("dplyr")
library("caret")
library("randomForest")
library("lattice")
library("ggplot2")
library("rpart")
library("e1071")
library("caret", lib.loc="/Library/Frameworks/R.framework/Versions/3.4/Resources/library")
library("stats")
library(relaimpo)
library(party)

```
Get a list of Variable names.

```{r}
Names <- names(dfNormDatAndFactor)
unlist(Names, recursive = TRUE, use.names = TRUE)
```

##Parrtitions created with 75% of data for training and 25% of data for testing.
```{r}
inTraining <- createDataPartition(dfNormDatAndFactor$Enrolling, p = 0.75, list = FALSE)
training <- dfNormDatAndFactor[inTraining, ]
testing <- dfNormDatAndFactor[-inTraining, ]
```

```{r}
training
```

```{r}
testing
```
##Run Random Forest Model with all variables.
```{r}
rfModel <- randomForest(Enrolling ~ Sex.F + Sex.M +Expel.N + Expel.Y+ First.Gen.N+ First.Gen.Y+Challenge.Tag.N + Challenge.Tag.Y+ Boettcher.Semi.N+ Boettcher.Semi.Y+ Boettcher.Final.N+Boettcher.Final.Y + Daniels.Semi.N+Daniels.Semi.Y+ Daniels.Final.N+ Daniels.Final.Y+ Harvey.App.N+ Harvey.App.Y + Harvey.Final.N+ Harvey.Final.Y+ FC.App.N+ FC.App.Y+  Thorson.App.N+ Thorson.App.Y+ Thorson.Admit.N +Thorson.Admit.Y+Summet.Participant.N+ Summet.Participant.Y + Mines.Medal.N+ Mines.Medal.Y+ SPS.N+ SPS.Y+ Veteran.N+ Veteran.Y+ Legacy.N +  Legacy.Y+ Athlete.N +  Athlete.N + Athlete.Y + State.CO +  State.Other  +  Citizenship.Foreign.National.International +Citizenship.International +  Citizenship.Missing+ Citizenship.U.S..Citizen+ Citizenship.U.S..Permanent.Resident.Green.Card.Holder+ Citizenship.Undocumented.DACA+ Ethnicity.American.Indian.or.Alaska.Native+  Ethnicity.Asian+ Ethnicity.Black.or.African.American+ Ethnicity.Hispanic.or.Latino + Ethnicity.Missing + Ethnicity.Multiracial +Ethnicity.Native.Hawaiian.or.Other.Pacific.Islander + Ethnicity.NotDeclared + Ethnicity.Unknown +Ethnicity.White+ Major.App.Applied.Mathematics...Statistics...Computational...Applied.Mathematics+ Major.App.Applied.Mathematics...Statistics...Statistics+ Major.App.Chemical.Engineering+ Major.App.Chemical.Engineering...Biological.Engineering.Specialty+ Major.App.Chemistry+  Major.App.Chemistry...Biochemistry.Specialty + Major.App.Chemistry...Environmental.Chemistry.Specialty + Major.App.Civil.Engineering + Major.App.Computer.Science + Major.App.Economics+ Major.App.Electrical.Engineering+ Major.App.Engineering.Physics+  Major.App.Environmental.Engineering+ Major.App.Geological.Engineering +  Major.App.Geophysical.Engineering +Major.App.Mechanical.Engineering +  Major.App.Metallurgical...Materials.Engineering + Major.App.Mining.Engineering +  Major.App.Missing + Major.App.Petroleum.Engineering+   Major.App.Undecided+ First.Contact.ACT +  First.Contact.Application + First.Contact.Athlete.Form + First.Contact.Campus.Visit + First.Contact.College.Fair + First.Contact.FUF+First.Contact.Girls.Lead.the.Way+First.Contact.GPA.Form + First.Contact.Inquiry.Form+First.Contact.Mailing+ First.Contact.Materials +  First.Contact.MEP+ First.Contact.Phone+ First.Contact.Preview.Mines+ First.Contact.Royall.Search+First.Contact.TOEFL+ First.Contact.SAT+ First.Visit.Campus.Tour+ First.Visit.Campus.Visit+ First.Visit.Class.Shadow +  First.Visit.Discover.Mines+ First.Visit.Discovery.Mines.in.Your.City+ First.Visit.Girls.Lead.the.Way+  First.Visit.Launch + First.Visit.Making.The.Connection + First.Visit.Meet.Me.at.Mines+ First.Visit.None+  First.Visit.Preview.Mines + First.Visit.Preview.Mines.In.Your.City + Sport.Men.s.Varsity.Baseball+  Sport.Men.s.Varsity.Basketball+  Sport.Men.s.Varsity.Football + Sport.Men.s.Varsity.Golf +Sport.Men.s.Varsity.Soccer+  Sport.Men.s.Varsity.Wrestling+  Sport.None+  Sport.Varsity.Swimming.Diving+ Sport.Varsity.Track.Field+Sport.Varsity.XCountry+  Sport.Women.s.Varsity.Basketball +  Sport.Women.s.Varsity.Soccer+  Sport.Women.s.Varsity.Softball + Sport.Women.s.Varsity.Volleyball+ App.Created.Days +  Age  + HS.GPA+ SATR.Converted +Review.OutsideActivity +Review.Leadership+Review.WorkExp+ Review.WorkEthic +Review.ExpDiversity +Review.DesireAttend +Review.Affinity+ Review.InnovEntrep+Review.Teamwork +Review.OverallFit + Logins.60Days+EventCount.All+EventCount.Admitted+EventCount.Campus, data =  training)
rfModel

```
```{r}
rfModel.prediction <- predict(rfModel, testing)
table(rfModel.prediction, testing$Enrolling)
```

To determine variable importance.
```{r}
imprfModel <-   importance(rfModel)
imprfModel
```
```{r}
#format((sort(imprfModel, decreasing=TRUE)), scientific=F)
#sort(imprfModel, decreasing=TRUE)  # relative importance
```
```{r}
dfimprfModel <-as.data.frame(imprfModel)
dfimprfModel
```


```{r}
confusionMatrix(table(rfModel.prediction, testing$Enrolling))
```

Plot of importance of Variabels.
```{r}
varImpPlot(rfModel,cex = .6, pt.cex = .7, color = "navy blue", gcolor = par("fg"), lcolor = "gray", main = "Variable Importance for Random Forest Model")
```
##Model with less variables
```{r}
rfModelLess <- randomForest(Enrolling ~ State.CO +  State.Other  +  Major.App.Mechanical.Engineering +  First.Contact.Application + First.Contact.Campus.Visit + First.Contact.FUF + First.Contact.Royall.Search+ First.Visit.Campus.Tour+ First.Visit.Campus.Visit+ First.Visit.Discover.Mines+ First.Visit.Launch + First.Visit.None+  First.Visit.Preview.Mines.In.Your.City + App.Created.Days +  Age  + HS.GPA+ SATR.Converted +Review.OutsideActivity +Review.Leadership+Review.WorkExp+ Review.WorkEthic +Review.ExpDiversity +Review.DesireAttend +Review.Affinity+ Review.InnovEntrep+Review.Teamwork +Review.OverallFit +Ethnicity.White +EventCount.All+EventCount.Admitted+EventCount.Campus, data =  training)
rfModelLess

```

```{r}
rfModelLess.prediction <- predict(rfModelLess, testing)
table(rfModelLess.prediction, testing$Enrolling)
```

To determine variable imortance.
```{r}
imprfModelLess <-   importance(rfModelLess)
#format(imprfModelLess, scientific=F)
imprfModelLess
```

```{r}
confusionMatrix(table(rfModelLess.prediction, testing$Enrolling))
```

##Model with top 25 variables
```{r}
rfModelTop25 <- randomForest(Enrolling ~ State.CO +  State.Other  +  First.Contact.Campus.Visit + First.Visit.Campus.Tour+ First.Visit.Campus.Visit+ First.Visit.Discover.Mines+ First.Visit.Launch + First.Visit.None+  First.Visit.Preview.Mines.In.Your.City + App.Created.Days +  Age  + HS.GPA+ SATR.Converted +Review.OutsideActivity +Review.Leadership+Review.WorkExp+ Review.WorkEthic +Review.ExpDiversity +Review.DesireAttend +Review.Affinity+ Review.InnovEntrep+Review.Teamwork +Review.OverallFit +EventCount.All+EventCount.Admitted+EventCount.Campus, data =  training)
rfModelTop25
```

```{r}
rfModelTop25.prediction <- predict(rfModelTop25, testing)
table(rfModelTop25.prediction, testing$Enrolling)
```

To determine variable imortance.
```{r}
imprfModelTop25 <-   importance(rfModelTop25)
#format(imprfModelLess, scientific=F)
imprfModelTop25
```

```{r}
confusionMatrix(table(rfModelTop25.prediction, testing$Enrolling))
```


```{r}
PredictionTop25 <- cbind(rfModelTop25.prediction,testing)
PredictionTop25
```











